Differences between classical and Bayesian inferences
- In the classical approach probability of an event is defined as
frequentist way while in Bayesian, the probability is defined on
subjective belief.
- In classical inferences data in hand is supposed to random
while the parameter is considered as constant. In contrast, the
parameter is considered as a random variable in bayesian.
- In Bayesian, we use posterior distribution to draw inferences
about the parameters while in the classical approach, we use the
likelihood function to draw inferences about the parameter.
Similarities between classical and Bayesian inferences
These two approaches are completely different from each other in
nature. If the prior distribution is non-informative or less
informative then both the approaches are identical to each
other.